Deep CNN and LSTM Architecture-Based Approach for COVID-19 Detection

The severe acute respiratory syndrome(SARS-CoV2) led to a pandemic of respiratory disease, namely COVID19. The disease has scaled worldwide and has become a global health concern. Unfortunately, the pandemic not just cost several individuals their lives but also, resulted in many people losing their jobs and life savings. In times like these, ordinary people become fearful of their resources in a world that gives its best resources to the wealthiest beings. Following the pandemic, the world suffered greatly and survival was rather difficult. As a result, numerous analytical techniques were developed to address this issue, with the key one being the discovery that the efficacy of clinically tested vaccines is actually quite poor. When researchers and medical professionals were unable to find a cure, radiologists and engineers created techniques to detect infected chests with the help of X-rays. Our proposed solution involves a CNN + LSTM model which has secured an accuracy of 98% compared to 95% of the trusted VGG-16 architecture. Our model's area under the curve (AUC) scores reached 99.458% while using RMSprop. A crucial feature of image processing till depth is accessible through scanning features from the layers of images using CNN. Our model uses 5 convolution blocks to detect the features. The coordination of activator functions, learning rates, and flattening has enabled accurate in-point predictions. With merely X-rays, models like ours ensure that anyone can easily detect covid-19. The best results obtained were at a learning rate =0.01 with RMSprop and Adam functions. The model has good fortune in detecting any other lung disease which occurs in the near future, as our data collectively rounds up to 4.5 gigabytes of data providing higher precision. © 2023 IEEE.

Domestic Violence against Women during the Covid-19: A Case Study of Bihar (India)

The Covid-19 pandemic revealed that the socioeconomic challenges in developing countries intersect within and beyond the dynamics of caste, class, space, and most importantly, gender. The recent outbreak of the Covid-19 pandemic compelled the entire human population to survive on the brink of uncertainty. The subsequent lockdown witnessed an upsurge in domestic abuse cases across the globe, making us realize how the four walls of the familial space turned into a hotbed of the 'shadow pandemic' resulting from the socioeconomic disparities and individual frustration during difficult times. India also witnessed a sudden surge in domestic violence cases, often called a shadow pandemic. While some got reported, many went without being documented in any forum. In this regard, this research is a case study of Bihar (India), which encountered a higher rate of domestic violence during the pandemic than other states such as Delhi, Haryana, Uttar Pradesh, and Himanchal Pradesh. This empirical study examines the economic, psychological, and social factors responsible for the surge in domestic abuse in Bihar during the Covid-19 pandemic © 2022. Journal of International Women''s Studies.All Rights Reserved

Leveraging Financial Inclusion Through Technology-Enabled Services Innovation: A Case of Economic Development in India

The majority of the Indian population is not getting the advantages of inclusive growth and development in India, referred to as financial inclusion, which has become a challenge for the Indian economy. The paper aims to investigate the use of available technology-enabled financial services and their role for financial inclusion in the current COVID-19 situation and the reaching of rural and semiurban India. The research is based on the in-depth analysis of the government policies and Fintech in the light of India's situation during COVID-19. The study reveals that the government showed the intent by opening a vast amount of banking accounts (411 million accounts) for financial inclusion in around six years. With radical changes in mobile subscribers and 4G, internet, and smartphone growth, India is close to achieving financial inclusion with full potential. However, significant change and development can be attained only if the government provides and motivates citizens to adopt the innovation services for financial inclusion. Copyright © 2022, IGI Global.

Psychological impact of domestic violence on women in India due to COVID-19

Purpose The COVID-19 outbreak has significant psychological effects because of reduced support system and social quarantine, making women the worst-hit population of shadow pandemic, i.e. domestic violence. While food shortages, unemployment and increased domestic-work burdens are the immediate effects of the lockdown, women at home have to bear its far-reaching impacts in the long term in the form of domestic abuse, making the study of the psychological impact of domestic violence against women imperative. This paper aims to identify the factors and causes responsible for domestic violence and its psychological impacts on women in different aspects. This paper further focuses on the reasons behind an escalation in psychological violence against women. Design/methodology/approach This paper is based on extrapolating data from various journal articles, Indian Government reports, newspaper articles and other printed materials that are recent, relevant and discuss domestic violence and mental stress during the COVID-19 pandemic. Researchers use Indian National Commission for Women's (NCW) data on complaints received regarding violence against women and domestic abuse in the year 2020 and 15 journal articles that discuss domestic violence against women during the COVID-19 period in different countries to discuss social inequalities and power relations impact on women' mental health. Findings The findings suggest that economic instability during the pandemic and social and cultural norms of India ignited psychological abuse against women during the pandemic. The number of monthly complaints of dowry death, dowry harassment and protection of women against domestic violence reflect on increased registered complaints in the postlockdown period in the year 2020. The number of monthly complaints received by the NCW from January 2020 to December 2020 in India represents that WhatsApp chat is a powerful tool for reporting domestic violence. Originality/value The pandemic lockdown has an adverse psychological impact on women, making them suffer from posttraumatic symptoms, substance abuse, panic attacks, depressions, hallucinations, eating disorders, self-harm, etc. This paper strives to reflect upon mitigation strategies to curb domestic violence in India.

Mobile robots in COVID-19

Robotics as a discipline focuses on combining perception with actions for human assistance in day-to-day lives and keeping them safe. Before COVID-19, mobile robots were limited mostly to the manufacturing industry, but with the present scenario, both demand and necessity have increased. Social distancing was required at all levels to flatten the pandemic curve, but it also had its challenges for essential services. With fewer working hands, the necessity to maintain social distancing directed us toward innovations in mobile robotics. The installation minimized human contact, substituted human in cleaning, sanitization, and delivery, and also monitored interactions and meetings. Various applications were developed as POC (Proof of Concept)in these difficult times to ensure safety and distancing. Ultraviolet (UV) robots disinfected the spaces, sanitizer spray robots are used in the manufacturing area, food and medicine delivery robots for hospitals, and, similarly, interaction and follow-me robots interacted with patients. It minimized the impact of COVID in hospitals, quarantine facilities, and manufacturing area. The distance was maintained from contaminated zones and allowed the workforce to focus on important tasks and continue the fight. Some applications also utilized perception and deep learning technologies to identify people with masks and perform thermal screenings. Mobile robots' potential has been realized and the horizon has widened. It has thus created an opportunity for advanced research in healthcare mobile robotics and low-cost indoor robotics by using innovative technologies. © 2021 River Publishers. All rights reserved.

Role of Sensors, Devices and Technology for Detection of COVID-19 Virus

The world is choking due to once-in-a-lifetime pandemic COVID-19 affecting about 9 million people and causing more than 4.5 lakh deaths worldwide and still counting. The causative agent named as SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has brought the human race to its knees and its activities to a grinding halt. The rapid transmissivity spearheaded by asymptomatic infectivity and spread are the key attributes for the success of the virus in establishing COVID-19 pandemic in a very short span. To tackle this unusual and extraordinary situation, the best bet left is rapid and robust detection of the pathogen. The present review understands the key biological properties of SARS-CoV-2 utilized to evolve facile, sensitive and robust detection techniques for COVID-19. The scope of the review includes the existing diagnostic techniques with their details from classical biological techniques like RT-PCR to most recent techniques involving novel biosensors, electronics tools, artificial intelligence, machine learning and Internet of Things (IoT). The review elaborates on key methods that can be employed in the future for better managing of the COVID-19 outbreak, thereby guarding against future pandemics. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Maslow theory revisited-Covid-19 - lockdown impact on consumer behaviour

The current study is attempting to derive the reference to the hierarchy of Maslow, where the consumers were placed before the arrival of Covid-19 and during the lockdown time. Consumer behavior consists of cognitive, emotional or physical activities in which people pick, purchase, consume and dispose of products and services to satisfy their choices and expectations. Abraham Maslow defined hierarchy of needs in different forms viz Physiological, Safety,Social,Esteem and Self-actualization needs. A multiplicity of competing factors influences human behaviour and thereby needs and requirements.Recognition of needs is essential as the initial step for market participants in the supply chain. At the same time recognising where the needs of consumers will alter is parallelly significant for smooth functioning of market processes and securing profitability along with capturing the trend. In the present study with the help of primary survey need recognition or any sort of variation therein, pre and during the Covid-19 lockdown periodare traced within the conceptual framework of Maslow Hierarchy of needs theory. © 2021 Karadeniz Technical University. All rights reserved.

Molecular Evaluation of COVID-19 in Pandemic Era

COVID-19 (SARS-CoV-2) has recently emerged as an ongoing pandemic disease or probably syndemic and became the latest threat to global health. The main route of transmission of virus droplet start with respiratory problems coughing, sneezing, fever during infection period, which may end up with death, if not treated. Many emerging epidemiological factors have made COVID-19 as global alarming disease. To control the outbreak of COVID-19, a critical management along with quarantine measure is applicable, which requires early detection of infection. The early detection of COVID-19 infection is playing a vital role in controlling of progression of illness and limiting viral spread within the population. Therefore, reliable, highly specific and sensitive diagnosis techniques are necessary for its early detection. Among several detection techniques, qRT-PCR is the rapidly employed, sensitive and widely accepted technique. In present review, different molecular techniques with emphasis on qRT-PCR for early diagnosis of emerging COVID-19 will be discussed.

A Study of Indian Stock Market using Matrix Variate Dynamic Model

Our aim is to study Indian stock market data using matrix variate dynamic model (MVDM). We need a model which preserves non-linear structure and the complexity of stock market data. MVDM has some structure preserving property which helps in understanding behaviour of stock data. We model MVDM by taking latent and observed data as a matrix variate with Gaussian noise. We use expectation maximization iterative techniques for parameter estimation. MVDM prediction accuracy is more except during major political events and COVID-19 period. © 2020 IEEE.

Impact of solar rooftop policy on residential consumers in state of Uttarakhand

Uttarakhand is bestowed with ample sunshine throughout the year, making solar power generation successful in the state. Despite the rapid scaling up of Solar Rooftop Systems connected to the grid in recent years, the actual benefits to residential consumers in the long run for using this technology has not been assessed. It is important for policy makers to fully recognizes which policy, or combination of policies, promoting solar PV applications has the greatest economic benefit. This paper aims to evaluate the impact of Uttarakhand state solar policy on residential consumers opting to install Rooftop solar systems connected to grid under net metering arrangement. Real-time energy consumption and generation data for 60 residential consumers have been studied to monitor cost benefit analysis of installed projects. The result shows the impact of policy is high on three factors;Monitory savings due to export of extra units generated, mitigation of issues of migration of local people from hills to cities in search of livelihood options and reduction in CO2 emissions due to clean generation in the state. © 2020, Central Board of Irrigation and Power. All rights reserved.